Find the perfect DevOps Engineers in Munich in minutes from over 15,000 CVs with the power of AI
Need support for CI/CD pipelines, Kubernetes operations, or cloud automation in Munich? Work with DevOps specialists who handle infrastructure as code, release engineering, observability, and platform reliability. Get fast, precise matching with vetted, available freelancers.
About the role
Delivery Focus
A DevOps Engineer connects software delivery with stable operations. Companies bring in this role to build reliable pipelines, automate infrastructure, and keep releases predictable. The work often spans cloud environments, container platforms, and deployment workflows across development, staging, and production.
- Design and improve CI/CD pipelines
- Set up infrastructure as code
- Support container orchestration and release automation
- Build monitoring, logging, and alerting setups
- Reduce manual work in build and deployment steps
Core Skills
Strong DevOps work needs both engineering skill and practical system thinking. A good DevOps Engineer understands how code moves through the delivery chain and where failures usually happen. They write clear automation, document setups, and work well with software teams, operations, and security.
- Cloud platforms such as AWS, Azure, or Google Cloud
- Kubernetes, Docker, and related orchestration tools
- Terraform, Ansible, or similar automation tools
- Git-based workflows and release processes
- Observability tools for metrics, logs, and traces
When To Bring One In
Freelance DevOps support is a good fit when a team needs specific expertise for a platform change, a migration, or a delivery bottleneck. It also helps when internal teams are overloaded and need hands-on help without a long hiring process. In Munich, this is common in software companies, industrial tech, mobility, and enterprise IT.
What Good Looks Like
A strong DevOps Engineer makes systems easier to run, not harder. They work cleanly, keep changes safe, and leave teams with setups they can maintain. Look for people who can explain trade-offs clearly and improve delivery without creating hidden complexity.
- Clear automation instead of fragile manual steps
- Stable pipelines that are easy to extend
- Practical security and access handling
- Calm incident support and thoughtful root-cause analysis
- Good handover, so the team can keep operating after the project
Meet FRATCH DevOps Engineers
Martin Wimmer
Senior AI Solution Architect
Last position:
Senior AI & DevOps Architect at DATEV
Azure AI Foundry, GitHub Copilot (Agent Mode), Model Context Protocol (MCP), Kubernetes, CloudFoundry, Terraform, GitHub Actions, Langfuse, Python, Grafana
Objective: Accelerate enterprise-wide developer enablement and migration from GitLab/Jenkins to GitHub through secure CI/CD standards and automated, agentic developer support.
- Architected & deployed an enterprise-grade AI Support Agent integrated into GitHub Copilot via MCP, enabling developers to query legacy Confluence docs and Git repositories contextually.
- Designed & standardized secure, reusable GitHub Actions "Golden Path" templates, accelerating onboarding and ensuring compliance-by-design for delivery teams.
- Built and engineered robust data pipelines to establish a DevOps Maturity Model, monitoring platform adoption and migration KPIs via Grafana and Azure Monitor.
- Established LLM observability and evaluation frameworks utilizing Langfuse and Azure Monitor to optimize agent responses and control token costs.
Thomas Hoefkens
Senior MLOps, DevOps Engineer
Last position:
Senior MLOps, DevOps Engineer at Trianel Energy
- Built and operated an end-to-end MLOps platform on Azure ML and Kubernetes (Kubeflow) for automated deployment, monitoring, and scaling of forecasting models (including Temporal Fusion Transformer, Informer, and Autoformer).
- Implemented CI/CD pipelines in Azure DevOps for the full ML lifecycle – from resource provisioning (Terraform) and data transformation (Hugging Face Datasets, Pandas, PyTorch, CUDA cluster) to training and evaluation, model registry, and endpoint deployment.
- Integrated MLflow for experiment tracking, model versioning, performance monitoring, and automated registration in the Azure Model Registry.
- Developed and containerized PyTorch training jobs (Azure Notebook, Jupyter Notebooks) for price and time series forecasting (PFC models) with automatic rollout via Azure ML Endpoints and REST/gRPC interfaces, Docker containerization, secured with OAuth 2.0.
- Set up monitoring and alerting mechanisms (Prometheus, MLflow Metrics), centralized logging, and cost monitoring.
- Automated infrastructure provisioning and model deployment using Terraform, Helm, and Azure CLI; connected to existing market data systems and event pipelines.
- Migrated existing workloads and databases (IONOS → Azure, MongoDB) and integrated them into central MLOps workflows and internal networks.
- Extended the platform with LLM-based tools (LangChain, LangServe) to integrate GPT-based analysis modules into existing Spring Boot services for market anomaly detection and automated reports.
- Analyzed and designed a software solution to efficiently process large volumes of data (>3000 messages/sec) (market data store).
- Developed Spring Boot / Java 21 container services with RabbitMQ to distribute exchange data through MongoDB (Kubernetes), with fast storage of data in Redis RMaps, deduplication, forwarding messages to Read Model queues, and building Read Models for UI display in MongoDB.
- Integrated RESTHeart to create a REST API for MongoDB.
- Built an Angular frontend to simplify data queries and master data maintenance.
- Agentic coding with remote and local LLMs (Claude Sonnet, Ollama Qwen) and MCP servers.
- Developed Python scripts to transform and clean incoming exchange data (Pandas, scikit-learn).
Ronald Mazelisz
DevOps Consultant
Last position:
DevOps Consultant at M.it services & systems GmbH
- Adjusting, optimizing, configuring, and administering a multi-stage GitLab instance with over 250 users
- Building, adjusting, expanding, and optimizing infrastructure, configuration, and monitoring
- Providing services and handing them over to production
- System environment: DependencyTrack, GitLab, Grafana, Hedgedoc, Kubernetes, OAuth2 Proxy, Openstack, Prometheus, Syseleven
Vitaliy Ryumshyn
DevOps GitOps (temp)
Last position:
DevOps GitOps (temp) at Signal Iduna
- Responsible for Openshift/Kubernetes on-prem administration and developer support.
- Developed URP infrastructure automation with Python, Ansible, Kustomize and ArgoCD, Argo Workflow/Events stack.
- Wrote smoke and load tests for URP infrastructure utilizing Python, Kustomize and ApplicationSets.
- Helped to set up and deploy URP infrastructure in Google Cloud, GKE.
- Set up monitoring for URP and ArgoCD stack with Splunk Cloud.
- Performed system administration tasks across RedHat Linux, Kubernetes/Openshift, ArgoCD, GitLab, Bitbucket Enterprise, Kafka and MongoDB.
Ales Loncar
Senior DevOps Consultant (Freelance)
Last position:
Senior DevOps Consultant (Freelance) at European Union Agency (via IBM)
- Worked as freelance Senior DevOps Consultant on-site for IBM at a European Union Agency, operating in a highly secure, air-gapped environment managing classified systems.
- Led automation and DevOps initiatives for a large-scale OpenShift platform (>400 nodes), driving deployment efficiency, GitOps adoption, and operational automation using Ansible, Python, and Bash while ensuring compliance with security requirements.
- Spearheaded automation of release and deployment workflows in a private cloud environment hosting 400+ OpenShift nodes, significantly improving deployment speed and reliability.
- Migrated existing playbooks, roles, and templates from Ansible Tower to Ansible Automation Platform (AAP), ensuring full compliance with fully-qualified collection names (FQCN) and preparing custom Execution Environments (EE) for containerized automation.
- Implemented GitOps Agent for AAP Controller Configuration as Code, enabling automated synchronization (CRUD) of Ansible Controller objects based on repository-stored configuration definitions using GitHub webhooks.
- Designed and automated complex multi-step operational workflows including environment cleanup, Helix cluster component re-creation, Kafka topic management, and OpenShift object lifecycle management across ~100 environments.
- Achieved a reduction of multi-day manual operations to under a few hours through automation improvements spanning multiple AAP clusters and OpenShift environments.
- Integrated Ansible Automation Platform with Thycotic (Delinea) Secret Server via lookup plugin to enhance secure credential management in automated processes.
- Managed deployment tasks, platform troubleshooting, and Istio network configurations while adhering to stringent EU PSC security and compliance standards.
- Collaborated with infrastructure and application teams to refine deployment procedures, develop naming conventions, and continuously improve automation coverage in an air-gapped, classified environment.
Daniel Redwig
Software Engineer
Last position:
Software Engineer at DB InfraGO AG
- Developed dynamic web components for displaying KPIs, intelligent map applications, and operational process analysis tools
- Angular 18+
- Leaflet, MapLibre
- NestJS, JavaScript, HTML, CSS
- PostgreSQL, GraphQL, RabbitMQ
- Gitea, Jenkins, Docker
Max Ritter
Cloud (AWS) | AI | DevOps | Data
Last position:
Cloud (AWS) | AI | DevOps | Data at Boehringer Ingelheim
- Architected and implemented an enterprise-grade AI Agent Platform leveraging Retrieval Augmented Generation (RAG) architecture to enhance clinical data insights.
- Established robust CI/CD pipelines for LLM applications using CDK and Jenkins, significantly reducing deployment times.
- Implemented comprehensive observability solutions that increased agent reliability across pharmaceutical environments.
- Designed scalable AI workflows with advanced orchestration that optimized context handling for enterprise data sources.
- Technologies: AI Agents (LangChain, LangGraph, Bedrock, Smolagents, Streamlit); LLM Operations (Tracing, Testing, Evaluation, LangSmith, LangFuse); Infrastructure-As-Code (AWS CDK, Terraform, Typescript, Jenkins); Vectors, Embeddings, RAG (OpenSearch, pgvector, PDF Extraction)
Frank Eppink
DevOps
Last position:
DevOps at Lauck-IT
Operations and extensions of Azure DevOps pipelines
Operations and extensions of AWS services
Citrix (Windows 10, Bitwarden)
AWS: ECR, EKS, CloudFront CDN, Route 53, VPC peering and CNI upgrade, Atlas MongoDB, S3 buckets, static website hosting
Azure: build and deploy with DevOps pipelines
Christian Trutz
JEE Software Engineer, DevOps Engineer
Last position:
JEE Software Engineer, DevOps Engineer at AKDB
- JEE Software Engineer
- DevOps Engineer
- Java, JEE, JBoss/WildFly, Vaadin, CI/CD Pipelines, Jenkins, Maven, Git, Oracle database, MSSQL Server database
Katarina Burghard
Lecturer in Project Management, Scrum and DevOps
Last position:
Lecturer in Project Management, Scrum and DevOps at velpTEC
- Workshops and professional support in adult education
Dominik Arnoldi
DevOps Engineer Freelancer
Last position:
IUeIvnOteprsnEatnigoinnaeleerHForechelsacnhcueler GmbH
- Migrated DataRobot into existing infrastructure
- Created AI infrastructure on AWS
- Migrated Bitbucket pipelines to GitLab
Josef Schermer
DevOps
Last position:
DevOps at Software house for an industrial company
- Implementation, maintenance and operation of an ERP system and a document exchange platform for a corrugated cardboard manufacturer.
- Tools and systems: Unix (Debian 6.x), C, SVN, Windows, C#, MS SQL Server, SCRUM.
Sebastian Fohler
Managing Director System Administration & DevOps
Last position:
Managing Director System Administration & DevOps at Far Galaxy Networks
- Windows application migration using Windows Server 2022/2025, DHCP, Active Directory, directory trust and setup, GPO management
- Cloud service automation, firewall and network management, debugging
Discover over 15,000 top freelancers
DevOps Engineers statistics
Typical experience
20 years
Average project duration
2.3 years
Certifications per freelancer
4
Top business areas
Information Technology, Product Development, Operations
Top industries
Information Technology, Manufacturing, Automotive
Most common languages
German, English, French
Bachelor's degree or higher
88%
Master's degree or higher
50%
Salary / Daily Rate Distribution
The chart shows how the daily rates of freelancers in this role are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Average rates for DevOps Engineers & Seniority distribution
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Frequently Asked Questions
Need clarity? Check out our simple overview of FRATCH
A DevOps Engineer sets up and improves the path from code to production. That usually includes CI/CD pipelines, infrastructure as code, container workflows, and monitoring. The goal is a delivery process that is repeatable, visible, and easier to operate.
Look for solid cloud knowledge, automation habits, and experience with deployment tooling. A good candidate should be comfortable with Kubernetes, Docker, Terraform, and Git-based workflows. They should also understand logging, alerting, and incident response, not just build scripts.
A DevOps Engineer focuses on the full delivery chain, not just server upkeep or cloud setup. Compared with a system administrator, the role is usually more automation-driven and closer to software teams. Compared with a cloud engineer, it often covers build, release, and operational practices as well as infrastructure.
Freelance support is a good choice when you need specialized help for a migration, pipeline rebuild, platform hardening, or a short delivery push. It also fits well if your team needs senior hands-on support before you define a longer-term operating model. A freelancer can start quickly and focus on the problem at hand.
Many DevOps tasks can be done remotely because the work lives in code, cloud consoles, and collaboration tools. On-site time in Munich can still help during sensitive migrations, incident work, or when a team needs close alignment with product and engineering leads. The right setup depends on access, security, and the pace of change.
The exact stack depends on the company, but the core tools are usually cloud services, Kubernetes, Docker, Terraform, CI/CD systems, and observability tools. A strong DevOps Engineer should also be comfortable with scripting and version control. What matters most is whether they can make the stack reliable and maintainable.
Ask for concrete examples of pipelines, environments, or platform changes they improved. Good candidates explain what they automated, what broke before, and how they reduced risk. You should also look for clear documentation, thoughtful decisions, and signs that they can work well with developers and operators.
Early deliverables often include a review of the current setup, a plan for the delivery pipeline, and a list of risks or bottlenecks. A DevOps Engineer may also provide quick wins such as cleaner build steps, better alerts, or a safer deployment flow. The best outcome is progress that the team can keep using after the engagement ends.
Request a Free Demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
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We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
